SCIENTIA GEOGRAPHICA SINICA ›› 2014, Vol. 34 ›› Issue (1): 25-31.doi: 10.13249/j.cnki.sgs.2014.01.25

• Orginal Article • Previous Articles     Next Articles

The Evolution of Network Structure of Inbound Tourist in Major Cities of China

Yao-feng MA1(), Zhi-hui LIN1,2(), Xian-feng LIU3, Lin MA1   

  1. 1.College of Tourism and Environment, Shaanxi Normal University, Xi’an, Shaanxi 710062, China
    2.Qingdao Tourism School, Qingdao, Shandong 266023, China
    3.College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China
  • Received:2012-11-05 Revised:2013-01-18 Online:2014-01-10 Published:2014-01-10


This article established the Inbound Tourist urban network that is linked by the model of tourist economic interrelationships employing GIS. Then the spatiotemporal evolution characteristics of Top1, Top5, Top10 networks in 1997 and 2010 were studied. The conclusions can be drawn as follows: 1) The network size is shrinking, but the maximum runoff and average runoff significantly grow, and the maximum runoff has occurred between Guangzhou and Shenzhen. 2) The agglomeration effect in a few core cities is more prominent. The structure of China inbound tourism is at the stage of core polarization, showing an overall “L” shaped distribution which means “the agglomeration effect of tourism in the eastern China is strong, but that in central and western China is weak”. Beijing, Shanghai, Guangzhou were the first class node cities, whose agglomeration effect significantly increased, Xi’an and Guilin were declined, while Shenzhen and Tianjin raised in 1997 and 2010. Agglomeration effect of cities in the eastern China was more obvious, while it declined in central and western China. The in-degree of cities in the western China was significantly higher than that in central China, but this advantage was reducing. That in the central China grew, but the economic interrelationship did not significant grow, still obviously lower than that in cities of the eastern and western China; 3) The in-degree and the strength of economic interrelationship were not proportional, Beijing’s in-degree was the highest, but its economic interrelationship was ranked only fourth, behind Guangzhou, Shenzhen and Shanghai. The first reason is the cities’ spatial distribution density, and the other is that the inbound tourism level of the two regions is very high, coupled with its relatively close distance. This also resulted in Zhuhai and Wuxi’s in-degrees were not high, but the economic interrelationships were very close; 4) From the bidirectional flow within the region and between regions, it is found that within the eastern area, the economic interrelationships are the highest and the most important relationship all over the country. The centers of the eastern China are Shanghai, Guangzhou, Beijing and Shenzhen. The centers of the western China are Xi’an, Chengdu, Chongqing and Guilin, whose relation with cities in the western China is very close, but that with other areas is not close. The centers of the central area are Changsha and Wuhan, whose relation with cities in the western is not close, but that with other areas is very close; 5) According to the network structure we can divide China inbound tourist urban into three systems: Beijing system, Shanghai system and Guangzhou system, which displays the patterns of “three centers, several cores”. Three centers are the first class node cities, Beijing, Shanghai and Guangzhou. Several cores are the second node and third node cities. The several cores of Beijing system are Tianjin, Xi’an, Qingdao and Dalian, the several cores of Shanghai system are Suzhou, Nanjing, Hangzhou, Changsha and Wuhan, and the several cores of Guangzhou system are Shenzhen, Zhuhai, Xiamen, Fuzhou, Chengdu, Chongqing and Guilin.

Key words: inbound tourist, urban network, economic interrelationships, China

CLC Number: 

  • F590